The proceedings contain 219 papers. The topics discussed include: security issues in blockchain integrated WSN: challenges and concerns;an intelligent stacking ensemble-based machine learning model for heart abnormali...
ISBN:
(纸本)9781665474139
The proceedings contain 219 papers. The topics discussed include: security issues in blockchain integrated WSN: challenges and concerns;an intelligent stacking ensemble-based machine learning model for heart abnormality;maximize the production process by using a novel hybrid model to predict the failure of machine;fall detection and activity recognition using hybrid convolution neural network and extreme gradient boosting classifier;strong and stable data communication using artificial intelligence method in mobile ad-hoc networks;blockchain industry 5.0: next generation smart contract and decentralized application platform;application of neural network in the prediction models of machine learning based design;brain tumor segmentation and survival prediction using multimodal MRI scans with deep learning algorithms;efficient integrity checking and secured data sharing in cloud;multimodal feature selection for android malware detection classifiers;intelligent face mask and body temperature detection system using machine learning algorithm;application of self-adaptive biogeography based optimization to economic load dispatch problems;and spotting web attack in IoT networks using ensemble deep learning technique.
As robots become smarter and more ubiquitous, optimizing the power consumption of intelligent compute becomes imperative towards ensuring the sustainability of technological advancements. Neuromorphic computing hardwa...
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ISBN:
(纸本)9798350377712;9798350377705
As robots become smarter and more ubiquitous, optimizing the power consumption of intelligent compute becomes imperative towards ensuring the sustainability of technological advancements. Neuromorphic computing hardware makes use of biologically inspired neural architectures to achieve energy and latency improvements compared to conventional von Neumann computing architecture. Applying these benefits to robots has been demonstrated in several works in the field of neurorobotics, typically on relatively simple control tasks. Here, we introduce an example of neuromorphic computing applied to the real-world industrial task of object insertion. We trained a spiking neural network (SNN) to perform force-torque feedback control using a reinforcement learning approach in simulation. We then ported the SNN to the Intel neuromorphic research chip Loihi interfaced with a KUKA robotic arm. At inference time we show latency competitive with current CPU/GPU architectures, and one order of magnitude less energy usage in comparison to traditional low-energy edge-hardware. We offer this example as a proof of concept implementation of a neuromoprhic controller in real-world robotic setting, highlighting the benefits of neuromorphic hardware for the development of intelligentcontrollers for robots.
The proceedings contain 168 papers. The topics discussed include: communication induced checkpointing based fault tolerance mechanism – a review and CIAC-FTM framework in IoT environment;a semantic review on challeng...
ISBN:
(纸本)9781665462006
The proceedings contain 168 papers. The topics discussed include: communication induced checkpointing based fault tolerance mechanism – a review and CIAC-FTM framework in IoT environment;a semantic review on challenges, trends towards defensive ids in Internet of things;semantic segmentation in medical image based on hybrid Dlinknet and UNet;smart car - one stop for all automobile needs;hybrid cryptography algorithm for the internet of things based plant information security;5G network: architecture, protocols, challenges and opportunities;fiber Bragg grating temperature sensor and calibration scheme in high magnetic field environment : an application for aluminum electrolysis cell in potline;federated learning with blockchain: a study of the latest decentralized couple;an enhanced copy-deterrence scheme for secure image outsourcing in cloud;decentralized data privacy protection and cloud auditing security management;land registry and title management using blockchain and smart contracts;breast cancer modeling and prediction combining machine learning and artificial neural network approaches;and confluence of artificial intelligence and blockchain powered smart contract in finance system.
intelligent business operation systems are undergoing a revolution as a result of cognitive computing, which is boosting their capacity to analyze large amounts of data and produce well-informed conclusions in real-ti...
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intelligent business operation systems are undergoing a revolution as a result of cognitive computing, which is boosting their capacity to analyze large amounts of data and produce well-informed conclusions in real-time. The purpose of this investigation is to investigate the possibility of incorporating cognitive computing technologies, such as machine literacy, natural language processing, and big data analytics, into business operation systems to address the issue of civic traffic, improve the flow of business, and enhance safety. The development of adaptive business control mechanisms that can respond robustly to changing business situations is made possible by cognitive computing. This is accomplished through the use of sophisticated algorithms and predictive analytics. The purpose of this article is to investigate case studies and real-world implementations, to highlight the major improvements in company efficiency and decrease in travel times that may be realized using cognitive computing. The findings provide evidence that cognitive computing has the potential to transform conventional business operation systems into intelligent, responsive networks that are capable of tone-optimization. This would result in the creation of civic environments that are more intelligent and more environmentally sustainable.
Demand response (DR) plays a significant role in modern energy management systems, particularly within the context of adaptive and intelligent building energy management systems (AI-BEMS). In the AI-BEMS context, DR f...
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ISBN:
(纸本)9798350361261;9798350361278
Demand response (DR) plays a significant role in modern energy management systems, particularly within the context of adaptive and intelligent building energy management systems (AI-BEMS). In the AI-BEMS context, DR focuses on dynamically adjusting energy usage in response to external factors, such as electricity prices, grid conditions, and environmental considerations. This survey paper explores the evolving landscape of DR within the framework of AI-BEMS, focusing on the integration of advanced technologies and adaptive strategies to optimize energy consumption and enhance grid reliability. This article reviews state-of-the-art research addressing the key concepts associated with integrating DR and AI-BEMS, including an overview of DR techniques in AI-BEMS, and an artificial intelligence and machine learning applications for the development of adaptive control strategies and DR optimization. Then, insights are provided on the future directions and the challenges in this field regarding the implementation of DR within AI-BEMS.
Fundamental in numerical computing, mean square (MS) and mean squared error (MSE) calculations play a vital role, especially in artificial intelligence (AI) and signal processing applications. This paper introduces a ...
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ISBN:
(数字)9798350349597
ISBN:
(纸本)9798350349603;9798350349597
Fundamental in numerical computing, mean square (MS) and mean squared error (MSE) calculations play a vital role, especially in artificial intelligence (AI) and signal processing applications. This paper introduces a versatile, low-complexity, and adaptable approach to implement MS and MSE calculations. The central concept involves employing in-memory computing (IMC) technique and executing computations through a set of memristor devices. Specifically, the necessary multiplications and additions leverage the inherent properties of memristor devices, adhering to Ohm's law and Kirchhoff's current law. This innovative method enhances flexibility by programming memristors and emphasizes processing efficiency by reducing computational complexity and latency, surpassing traditional implementation methods.
This study considered a method of applying model predictive control (MPC) to a system whose dynamics are unknown, using the dynamics estimated by an extended state observer (ESO). In our approach, the dynamics require...
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intelligent transportation systems (ITS) use the latest technologies for real-time traffic control and monitoring to ensure efficient traffic management and reduce the risks of traffic accidents. The microscopic level...
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ISBN:
(纸本)9798350369458;9798350369441
intelligent transportation systems (ITS) use the latest technologies for real-time traffic control and monitoring to ensure efficient traffic management and reduce the risks of traffic accidents. The microscopic level of traffic modeling is the most appropriate level for controlling and monitoring the interaction between vehicles based on car-following scenarios. However, the data retrieved from sensor networks can be affected by measurement errors, and consequently the implementation of appropriate mechanisms to overcome their propagation to the control system is mandatory. This paper aims to analyse the current research in the calibration of car-following models and provide valuable insights of recent developments in this field. To achieve this goal, VOSviewer has been chosen as a visualisation tool to create bibliographic maps based on the output from the well-known scientific database Clarivate Analytics Web of Science (WoS). The maps obtained provide a visual representation of the main institutions involved in this field of research and identify the research interests based on author and indexing keywords. Furthermore, this paper analyses the top five clusters identified based on the analysis of co-occurrence keywords, presenting discussions about the connections existing within these clusters.
The proceedings contain 170 papers. The topics discussed include: analysis and prediction of learning effect based on data mining algorithm and sports system;evaluation of rural revitalization based on projection purs...
ISBN:
(纸本)9781665493963
The proceedings contain 170 papers. The topics discussed include: analysis and prediction of learning effect based on data mining algorithm and sports system;evaluation of rural revitalization based on projection pursuit model;application of particle swarm optimization algorithm in system economic scheduling;design of video stream encoding in microfilm;the application of the expert system in English reading teaching;the application analysis of virtual and augmented reality in modern drama, film and television;logistics distribution route optimization algorithm based on deep learning;design of English teaching system based on K-mean clustering algorithm;financial abnormal data monitoring and analysis algorithm based on data mining and neural network;the application of grow model in vocal music teaching;the application of video flow graph in the construction of educational network platform;construction of financial early warning system based on binary time series algorithm;terrain feature extraction method of digital transmission line based on depth self-encoder;research and design of English auxiliary learning system based on human-computer interaction;and application of resource coordination and management in data network in innovation and entrepreneurship education system.
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